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Last scan 2026-09-15 Models tracked 259 Providers 32 Cheapest paid Granite 4.0 H Micro $0.017/Mtok in Every price links to its source

MiniMax-M2.1

by MiniMax

Retired budget open weights cheap tier
Email me when MiniMax-M2.1 gets cheaper
Retired on . No longer served on the endpoint we price — the figures below are kept for historical reference only. Replaced by MiniMax-M2.7. Full retirement status & replacements →
Availability: MiniMax's Pay-as-You-Go pricing page (checked 2026-07-28) lists MiniMax-M2.1 under 'Legacy Models', not among its actively-offered text LLMs (which are MiniMax-M3 and MiniMax-M2.7). The $0.30/$1.20 shown is a real historical price — it still appears on the Legacy row and LiteLLM carries minimax/MiniMax-M2.1 at the same value — but M2.1 is no longer the current offering, so treat it as superseded by MiniMax-M2.7. This is a lifecycle reclassification; the price itself did not change.

Today's price · per 1M tokens

Input

$0.300

per 1M tokens

Output

$1.20

per 1M tokens

Blended

$0.525

blended $/1M — 3:1 weighted input:output

Cached input

$0.030

10% of input — prompt caching

Source: official MiniMax pricing · read MODELPRICEWATCH.COM · 2026-09-15

Price receipt

Historical price.This model is retired — withdrawn on — so the provider no longer sells it and its page can no longer confirm this number: a price for a model no longer on sale is unconfirmable by definition, not missing. The figures above are the last prices we recorded for this model, kept as a historical record rather than a live quote.

Overview

MiniMax M2.1 model. $0.30/$1.20 per 1M; cached $0.03. Superseded by MiniMax-M2.7.

Run it yourself

Deploy this open model on rented GPUs

Open weights mean you can self-host instead of paying per-token API prices. These platforms let you serve it on demand — often cheaper at scale.

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Capabilities

struck through = not supported
Input 1/5
Text ✓ Image Audio Video PDF
Output 1/5
Text ✓ Image Audio Video Embedding
Features 3/9
Prompt caching ✓ Reasoning Coding Fast inference Long context ✓ Open weights ✓ Multimodal Web search Realtime

Benchmark performance

accuracy % · higher is better
Percentile vs all tracked models 23.7th2 independent measurements
Percentile per $/Mtok 45.6

We hold no per-benchmark accuracy scores for this model yet, so it has no accuracy average. That is a gap in our coverage, not a sign the model is untested — independent evaluators often publish a composite index for a new model long before releasing its per-benchmark numbers. The percentile above is its standing across the independent composites below.

Independent composite scores
  • AA-Omniscience Index: -32.9 (−100–100)
  • LMSYS Chatbot Arena: 1383.8 ELO (Human preference)
How it stacks up
  • Ranks #135 of 181 comparably-measured models by percentile score, across 2 independent measurements
  • Ranks #57 of 181 comparably-tested models by normalized performance per dollar

Source: Artificial Analysis, LMSYS Chatbot Arena (UC Berkeley) · updated · See full rankings →

Specifications

Provider
MiniMax
Context window
205K tokens
Modality
text
Parameters
Proprietary
Open source
Yes — open weights available
Released
Status
Retired ended
Last updated
Tags
open-weightsbudgetcachingretired

Availability verified: — per MiniMax's own deprecation notice

Try on MiniMax Official pricing page